We suggest a theoretical basis for the comparative evaluation of forecasts. Instead of the general assumption that the data is generated from a stochastic model, we classify three stages of prediction experiments: pure non-stochastic prediction of given data, stochastic prediction of given data,...

This paper examines the long-run dynamics and the cyclical structure of the US stock market using fractional integration techniques, specifically a version of the tests of Robinson (1994a) which allows for unit (or fractional) roots both at the zero (long-run) and at the cyclical frequencies. We...

The occurrence of decision problems with changing roles of null and alternative hypotheses has increased interest in extending the classical hypothesis testing setup. Particularly, confirmation analysis has been in the focus of some recent contributions in econometrics. We emphasize that...

For many economic time-series variables that are observed regularly and frequently, for example weekly, the underlying activity is not distributed uniformly across the year. For the aim of predicting annual data, one may consider temporal aggregation into larger subannual units based on an...

We investigate whether and to what extent multiple encompassing tests may help determine weights for forecast averaging in a standard vector autoregressive setting. To this end we consider a new test-based procedure, which assigns non-zero weights to candidate models that add information not...

We consider a nonparametric test for the null of seasonal unit roots in quarterly time series that builds on the RUR (records unit root) test by Aparicio, Escribano, and Sipols. We find that the test concept is more promising than a formalization of visual aids such as plots by quarter. In order...

The problem of detecting unit roots in univariate and multivariate time series data is treated as a problem of multiple decisions instead of a testing problem, as is otherwise common in the econometric and statistical literature. Four examples for such multiple decision designs are considered:...

We propose a bivariate structural time series framework to decompose GDP and the unemployment rate into their trend, cyclical, and irregular components. We implement Okun's law by a generalised version of the common cycles restriction allowing for a phase shift between the two cycles and add a...

Modelling the growth rate of economic time series with a Markov switching process in their mean and/or their variance allows to take account of two facts that are often encountered in such series, namely that the periods in which each mean is prevailing differ in their duration and that the...

This paper deals with optimal window width choice in non-parametric lag- or spectral window estimation of the spectral density of a stationary zero-mean process. Several approaches are reviewed: the cross-validation based methods described by Hurvich (1985), Beltrao & Bloomfield (1987) and...